Our group has 8 full papers at the upcoming CHI Conference on Human Factors in Computing Systems 2017, with one or several people from our group as authors. They cover exciting topics, ranging from machine learning techniques for inverse modeling, to modeling learning of new UI layouts to design implications for practical eye gaze applications, and more.

• What is Interaction?

  Kasper Hornbæk, University of Copenhagen, Denmark
  Antti Oulasvirta, Aalto University, Helsinki, Finland
  

  Abstract: The term interaction is field-defining, yet surprisingly confused. This essay discusses what interaction is. We first argue that only few attempts to directly define interaction exist. Nevertheless, we extract from the literature distinct and highly developed concepts, for instance viewing interaction as dialogue, transmission, optimal behavior, embodiment, and tool use. Importantly, these concepts are associated with different scopes and ways of construing the causal relationships between the human and the computer. This affects their ability to inform empirical studies and design. Based on this discussion, we list desiderata for future work on interaction, emphasizing the need to improve scope and specificity, to better account for the effects and agency that computers have in interaction, and to generate strong propositions about interaction.

• Modelling Learning of New Keyboard Layouts

  Jussi Jokinen , Aalto University, Helsinki, Finland
  Sayan Sarcar, Kochi University of Technology, Kochi, Japan
  Antti Oulasvirta , Aalto University, Helsinki, Finland
  Chaklam Silpasuwanchai , Kochi University of Technology, Kochi, Japan
  Zhenxin Wang , Kochi University of Technology, Kochi, Japan
  Xiangshi Ren , Kochi University of Technology, Kochi, Japan

  Abstract: Predicting how users learn new or changed interfaces is a long-standing objective in HCI research. This paper contributes to understanding of visual search and learning in text entry. With a goal of explaining variance in novices’ typing performance that is attributable to visual search, a model was designed to predict how users learn to locate keys on a keyboard: initially relying on visual short-term memory but then transitioning to recall-based search. This allows predicting search times and visual search patterns for completely and partially new layouts. The model complements models of motor performance and learning in text entry by predicting change in visual search patterns over time. Practitioners can use it for estimating how long it takes to reach the desired level of performance with a given layout.

• Inferring Cognitive Models from Data using Approximate Bayesian Computation

  Antti Kangasrääsiö , Aalto University, Espoo, Finland
  Kumaripaba Athukorala , Aalto University, Helsinki, Finland
  Andrew Howes , University of Birmingham, UK
  Jukka Corander, University of Oslo, Norway
  Samuel Kaski , Aalto University, Helsinki, Finland
  Antti Oulasvirta , Aalto University, Helsinki, Finland
  

  Abstract: An important problem for HCI researchers is to estimate the parameter values of a cognitive model from behavioral data. This is a difficult problem, because of the substantial complexity and variety in human behavioral strategies. We report an investigation into a new approach using approximate Bayesian computation (ABC) to condition model parameters to data and prior knowledge. As the case study we examine menu interaction, where we have click time data only to infer a cognitive model that implements a search behaviour with parameters such as fixation duration and recall probability. Our results demonstrate that ABC (i) improves estimates of model parameter values, (ii) enables meaningful comparisons between model variants, and (iii) supports fitting models to individual users. ABC provides ample opportunities for theoretical HCI research by allowing principled inference of model parameter values and
  their uncertainty.

• Toward Everyday Gaze Input: Accuracy and Precision of Eye Tracking and Implications for Design

  Anna Feit , Aalto University, Helsinki, Finland
  Shane Williams , Microsoft Research, Redmond, Washington, United States
  Arturo Toledo , Microsoft Research, Redmond, Washington, United States
  Ann Paradiso , Microsoft Research, Redmond, Washington, United States
  Harish Kulkarni , Microsoft Research, Redmond, Washington, United States
  Shaun Kane , University of Colorado, Boulder, CO, United States
  Meredith Morris , Microsoft Research, Redmond, Washington, United States

  Abstract: For eye tracking to become a ubiquitous part of our everyday interaction with computers, we first need to understand its limitations outside rigorously controlled labs, and develop robust applications that can be used by a broad range of users and in various environments. Toward this end, we collected eye tracking data from 80 people in a calibration-style task, using two different trackers in two lighting conditions. We found that accuracy and precision can vary between users and targets more than six-fold, and report on differences between lighting, trackers, and screen regions. We show how such data can be used to determine appropriate target sizes and to optimize the parameters of commonly used filters. We conclude with design recommendations and examples how our findings and methodology can inform the design of error-aware adaptive applications.

• WatchSense: On- and Above-Skin Input Sensing through a Wearable Depth Sensor

  Srinath Sridhar,  Max Planck Institute for Informatics, Saarbrücken, Germany
  Anders Markussen , University of Copenhagen, Copenhagen, Denmark
  Antti Oulasvirta , Aalto University, Helsinki, Finland
  Christian Theobalt , Max Planck Institute for Informatics, Saarbrücken, Germany
  Sebastian Boring , University of Copenhagen, Copenhagen, Denmark, Denmark

  Abstract: This paper contributes a novel sensing approach to support on-and above-skin finger input for interaction on the move. WatchSense uses a depth sensor embedded in a wearable device to expand the input space to neighboring areas of skin and the space above it. Our approach addresses challenging camera-based tracking conditions, such as oblique viewing angles and occlusions. It can accurately detect fingertips, their locations, and whether they are touching the skin or hovering above it. It extends previous work that supported either mid-air or multitouch input by simultaneously supporting both. We demonstrate feasibility with a compact, wearable prototype attached to a user’s forearm (simulating an integrated depth sensor). Our prototype—which runs in real-time on consumer mobile devices—enables a 3D input space on the back of the hand. We evaluated the accuracy and robustness of the approach in a user study. We also show how WatchSense increases the expressiveness of input by interweaving mid-air and multitouch for several interactive applications.

• Evaluation of Prototypes and the Problem of Possible Futures

  Antti Salovaara, University of Helsinki, Helsinki, Finland
  Antti Oulasvirta, AaltoUniversity, Helsinki, Finland
  Giulio Jacucci, University of Helsinki, Helsinki, Finland

  Abstract: There is a blind spot in HCI’s evaluation methodology: we rarely consider the implications of the fact that a prototype can never be fully evaluated in a study. A prototype under study exists firmly in the present world, in the circumstances created in the study, but its real context of use is a partially unknown future state of affairs. This present-future gap is implicit in any evaluation of prototypes, be they usability tests, controlled experiments, or field trials. A carelessly designed evaluation may inadvertently evaluate the wrong futures, contexts, or user groups, thereby leading to false conclusions and expensive design failures. The essay analyses evaluation methodology from this perspective, illuminating how to mitigate the present-future gap.

• Modeling User Performance on Curved Constrained Paths

  Mathieu Nancel, University of Waterloo, Aalto University, Inria Lille
  Edward Lank, University of Waterloo, University of Lille

  Abstract: In 1997, Accot and Zhai presented seminal work analyzing the temporal cost and instantaneous speed profiles associated with movement along constrained paths. Their work posited and validated the _steering law_, which described the relationship between path constraint, path length and the temporal cost of path traversal using a computer input device (e.g. a mouse). In this paper, we argue that the steering law fails to correctly model constrained paths of varying, arbitrary curvature, propose a new form of the law that accommodates these curved paths, and empirically validate our model.

• Utilizing Experience Goals in Design of Industrial Systems

  Virpi Roto , School of Arts, Design and Architecture, Aalto University, Helsinki, Finland
  Eija Kaasinen , VTT Technical Research Centre of Finland Ltd., Tampere, Finland
  Tomi Heimonen , University of Wisconsin-Stevens Point, Stevens Point, Wisconsin, USA
  Hannu Karvonen , VTT Technical Research Centre of Finland Ltd., Tampere, Finland
  Jussi Jokinen ,  Aalto University, Espoo, Finland
  Petri Mannonen,  Aalto University, Espoo, Finland
  Hannu Nousu , KONE Corporation, Helsinki, Finland
  Jaakko Hakulinen , University of Tampere, Tampere, Finland, et al.

  Abstract: The core idea of experience-driven design is to define the intended experience before functionality and technology. This is a radical idea for companies that have built their competences around specific technologies. Although many technology companies are willing to shift their focus towards experience-driven design, reports on real-life cases about the  utilization of this design approach are rare. As part of an industry-led research program, we introduced experience-driven design to metal industry companies with experience goals as the key technique. Four design cases in three companies showed that the goals are useful in keeping the focus on user experience, but several challenges are still left for future research to tackle. This exploratory research lays ground for future research by providing initial criteria for assessing experience design tools. The results shed light on utilizing experience goals in industrial design projects and help practitioners in planning and managing the product design process with user experience in mind.

Links to the PDFs and more info coming soon.